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deep_analysis

Analyze ACP agent addresses to identify risk signals, behavioral patterns, and percentile rankings for comprehensive due diligence.

Instructions

Get deep trust analysis for an ACP agent address. Returns detailed breakdown with percentile rankings, risk signals, and behavioral patterns. Use this for thorough due diligence.

Input Schema

TableJSON Schema
NameRequiredDescriptionDefault
addressYesEthereum/Base wallet address (0x...) of the agent

Implementation Reference

  • Implementation of the "deep_analysis" MCP tool which queries the Maiat SDK's 'sdk.deep' method.
    // ---- Tool: deep_analysis ----
    server.tool(
      "deep_analysis",
      "Get deep trust analysis for an ACP agent address. Returns detailed breakdown with percentile rankings, risk signals, and behavioral patterns. Use this for thorough due diligence.",
      {
        address: z
          .string()
          .describe("Ethereum/Base wallet address (0x...) of the agent"),
      },
      async ({ address }) => {
        try {
          const data = await sdk.deep(address);
          return {
            content: [
              {
                type: "text" as const,
                text: JSON.stringify(data, null, 2),
              },
            ],
          };
        } catch (err) {
          return {
            content: [
              {
                type: "text" as const,
                text: JSON.stringify({
                  error: err instanceof Error ? err.message : String(err),
                  address,
                }),
              },
            ],
          };
        }
      }
    );
Behavior2/5

Does the description disclose side effects, auth requirements, rate limits, or destructive behavior?

With no annotations provided, the description carries full burden for behavioral disclosure. It mentions the tool 'returns detailed breakdown' but doesn't specify response format, potential errors, rate limits, authentication needs, or whether it's read-only or mutative. The phrase 'deep trust analysis' is vague about what the analysis entails operationally.

Agents need to know what a tool does to the world before calling it. Descriptions should go beyond structured annotations to explain consequences.

Conciseness4/5

Is the description appropriately sized, front-loaded, and free of redundancy?

The description is appropriately concise with two sentences: the first states purpose and outputs, the second provides usage guidance. It's front-loaded with key information and has no wasted words, though it could be slightly more structured (e.g., separating outputs into a list).

Shorter descriptions cost fewer tokens and are easier for agents to parse. Every sentence should earn its place.

Completeness3/5

Given the tool's complexity, does the description cover enough for an agent to succeed on first attempt?

For a single-parameter tool with no output schema and no annotations, the description is minimally adequate. It covers what the tool does and when to use it at a high level, but lacks details on return values, error conditions, or behavioral constraints that would be helpful given the absence of structured metadata.

Complex tools with many parameters or behaviors need more documentation. Simple tools need less. This dimension scales expectations accordingly.

Parameters3/5

Does the description clarify parameter syntax, constraints, interactions, or defaults beyond what the schema provides?

Schema description coverage is 100%, so the schema already documents the single 'address' parameter as an 'Ethereum/Base wallet address'. The description adds no additional parameter semantics beyond implying it's for an 'ACP agent address', which aligns with but doesn't expand upon the schema. Baseline 3 is appropriate given high schema coverage.

Input schemas describe structure but not intent. Descriptions should explain non-obvious parameter relationships and valid value ranges.

Purpose4/5

Does the description clearly state what the tool does and how it differs from similar tools?

The description clearly states the tool's purpose: 'Get deep trust analysis for an ACP agent address' with specific outputs ('detailed breakdown with percentile rankings, risk signals, and behavioral patterns'). It distinguishes from simpler siblings like 'get_agent_reputation' or 'get_agent_trust' by emphasizing thoroughness, though it doesn't explicitly name those alternatives.

Agents choose between tools based on descriptions. A clear purpose with a specific verb and resource helps agents select the right tool.

Usage Guidelines3/5

Does the description explain when to use this tool, when not to, or what alternatives exist?

The description provides implied usage guidance: 'Use this for thorough due diligence' suggests it's for comprehensive analysis rather than quick checks. However, it doesn't explicitly state when to choose this over siblings like 'get_agent_trust' or 'get_agent_reputation', nor does it mention any prerequisites or exclusions.

Agents often have multiple tools that could apply. Explicit usage guidance like "use X instead of Y when Z" prevents misuse.

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